The web has an enormous collection of live
cameras view image parks, roads, cities, beaches, mountains, ski-resorts, buildings
and more. Over the last 5 years, I have been archiving imagery from most (>25000)
publically available outdoor cameras, and working to understand how to
effectively use this massively distributed resource as a tool for phenology,
environmental and atmospheric measurement.

Because these cameras are fixed in place
and watch the same scene over time, this set of images is highly
structured. Because of this structure,
simple algorithms based on PCA can be used for diverse purposes such as
geo-locating where in the world a camera is, solving for the 3D structure of
the scene in view, or segmenting the scene into component parts. With extra information for each image such as
the wind direction or sun direction, then methods based on Canonical
Correlation Analysis can solve for the relative orientation of the camera, and
the surface normal of parts of the scene.
I will conclude with some of the challenges we continue to face in
working with these half-a-billion images.